Journal Article

A multi-year study investigated the impact of incorporating student-directed
discovery projects into introductory statistics courses. Pilot instructors at institutions
across the United States taught statistics implementing student-directed projects with
the help of a common set of instructional materials designed to facilitate such
projects. Researchers measured the impact of these projects on student learning and
on students’ attitudes and beliefs about statistics. Results of the quantitative analyses
are shared, with subsequent discussion of their implications. Findings suggest that
inclusion of student-directed research projects in introductory statistics can lead to
greater statistics self-efficacy and improved statistical knowledge in specific domains.
Additional analyses suggest that these student benefits may improve as their
instructors gain more experience facilitating such projects.

The purpose of this study is to adapt the Survey of Attitudes Towards Statistics
(SATS-36) for Estonian secondary school students in order to develop a valid
instrument to measure students’ attitudes within the Estonian educational context.
The SATS-36 was administered to Estonian-speaking secondary school students
before their compulsory statistics course. Because the fit indices for confirmatory
factor analysis did not indicate a good fit, an exploratory factor analysis was
conducted to find a new model. It validated a four-factor structure of the scale,
excluding nine items. Good indices for both reliability and validity were obtained.
Trends in secondary school students’ attitudes were also examined to investigate the
effects of gender and gender combined with the level of education. Results showed
that students tended to feel rather positively about statistics at the beginning of the
course. All four factors displayed differences between boys and girls. Comparison of
lower and upper secondary level students showed that students from the upper
secondary level value statistics more highly. The authors recommend SATS with some
small proposed changes to make it even more suitable for the secondary level.

Full Fact is an independent, non-partisan fact-checking charity. A particular
focus is the analysis of factual claims in political debate in the UK; for example, fact checking claims and counterclaims made during Prime Minister’s questions. Facts do
not appear in a vacuum as they are often used as key elements in an effort to make a
coherent argument. This paper describes a number of case histories where facts are
disputed, drawn from our election work, to give an overview of the contemporary
state of statistical literacy among politicians and the media. Common pitfalls in
politicians’ claims are set out, along with descriptions of our attempts to close the
communication gap between different communities.

Statistical literacy is complex and multifaceted. In every country, education and
numeracy are a function of a multitude of factors including culture, history, and
societal norms. Nevertheless, since the launch of the International Statistical Poster
Competition (ISLP) in 1994, a number of patterns have emerged to suggest there are
some common or universal success factors in running statistical literacy competitions
involving schools, universities, statistical offices, and many other institutions. This
paper outlines some of those factors, such as institutional cooperation, celebrating
participation and success, improvement of statistical literacy in the local schools,
support for teachers, the involvement of national statistics institutes, and use of
technology. These factors have been identified from our own experience running the
competition and from articles submitted to the ISLP newsletters. Statistical literacy is
a complex phenomenon, and so this is neither an exhaustive list of key factors nor a
formula for success, but rather an overview of recurring themes across countries
participating in the competition around the world.

Statistical literacy increasingly is considered an important outcome of schooling.
There is little information, however, about appropriate expectations of students at
different stages of schooling. Some progress towards this goal was made by Watson
and Callingham (2005), who identified an empirical 6-level hierarchy of statistical
literacy and the distribution of middle school students across the levels, using
archived data from 1993-2000. There is interest in reconsidering these outcomes a
decade later, during which statistics and probability has become a recognised strand
of the Australian mathematics curriculum. Using a new data-set of over 7000 student
responses from middle-years students in different parts of Australia during the period
2007-2009, the nature of the hierarchy was confirmed. Longitudinal analysis
identified how students performed across time against the hierarchy. Suggestions are
made for systems and teachers about realistic expectations for middle-years students,
and possible curriculum challenges.

In recent years, research on teaching and learning of statistics emphasized that
the interpretation of data is a complex process that involves cognitive and technical
aspects. However, it is a human activity that involves also contextual and affective
aspects. This view is in line with research on affectivity and cognition. While the
affective aspects are recognized as important for the interpretation of data, they were
not sufficiently discussed in the literature. This paper examines topics from an
empirical study that investigates the influence of affective expression during the
interpretation of statistical data by final-year undergraduate students of statistics and
pedagogy. These two university courses have different curricular components, which
are related to specific goals in the future professional careers of the students. The
results suggest that despite differing academic backgrounds in both groups, the
participants’ affective expressions were the most frequent type of category used
during the interpretation of research assignments.

Statistical information pervades everyday life in the twenty-first century.
Research shows, however, that the skills needed to be able to understand and
critically evaluate statistical information must be specifically taught. In 2013, an
externally assessed National Certificate in Educational Achievement standard in
statistical literacy was introduced for the first time in New Zealand. A small
exploratory study investigated a possible teaching approach designed to enable Year-
13 students (aged 17-18) to critically evaluate media reports. Findings suggest that
the learning trajectory required several key components including media reports as
both a motivational and conceptual development tool. In addition, computer
visualizations and procedural scaffolds appeared valuable tools for facilitating
conceptual understanding of the margin of error.

Opening Real Science (ORS) is a three-year government initiative developed as
part of the Mathematics and Science Teachers program. It is a collaboration across
universities involving teacher educators, scientists, mathematicians, statisticians and
educational designers aimed at improving primary and secondary pre-service
teachers’ competence and confidence in mathematics and science. The ORS project
has developed 25 online learning modules for pre-service teacher programs.
Statistical literacy is prioritised. The Statistical Literacy Module for Primary
Teachers (SL-P) adopts an inquiry-based approach and uses resources and contexts
relevant to their practice. This paper documents the development and evaluation
process of SL-P from its conception to implementation, and reviews the initial trials .

The issue of poor statistical literacy amongst undergraduates in the United Kingdom is well documented. At university level, where poor statistics skills impact particularly on social science programmes, embedding is often used as a remedy. However, embedding represents a surface approach to the problem. It ignores the barriers to learning that students bring to class, which may not always be addressed solely through embedding, such as, mathematics anxiety. Instead, embedding can only work within a much deeper pedagogic model that places students at its heart, as active participants in learning. This paper examines the development of such a model within a large sociology programme, where there was an implementation of a range of pedagogic strategies to support the development of students’ statistical literacy.

In British social science degree programmes, methods courses have a bad press,
and statistics courses in particular are not well-liked by most students.

A nationally coordinated, strategic investment in quantitative skills training, Q-Step, is an attempt
to address the issues affecting the shortage of quantitatively trained humanities and
social science graduates. Pedagogic approaches to teaching statistics and data
analysis to social science students are starting to indicate positive outcomes. This
paper contributes to these debates by focusing on the perspective of the student
experience in different learning environments: first, we explain the approach taken at
the University of Manchester to teaching a core quantitative research methods
module for second-year sociology students; and second, we introduce case studies of
three undergraduates who took that training and went on to work as interns with
social research organisations, as part of a Manchester Q-Step Centre initiative to
take learning from the classroom into the workplace.